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A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks

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  • Chen, Chien-Ming

Abstract

A production network can be described as a collection of production processes performed by several interdependent groups of sub decision-making units (SDMUs) within a DMU. Dynamic effects pertain to the situation where intermediate outputs consumed by one SDMU may also dynamically influence its output level in the future. Without considering these effects in efficiency measurement, we would obtain biased efficiency measurement, because the measure could not faithfully reflect the underlying performance. Hence the result would provide misleading information to decision-makers. This paper proposes a network-DEA model with new efficiency measures to systematically cope with the dynamic effect within a production network. Various interconnections between the new measure and the DEA-efficiency have also been established. Additionally, we also formalize the relationship between returns-to-scale properties of DMUs and those of its constituting SDMUs. This paper presents a unified framework to analyze performances in a dynamic production network.

Suggested Citation

  • Chen, Chien-Ming, 2009. "A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks," European Journal of Operational Research, Elsevier, vol. 194(3), pages 687-699, May.
  • Handle: RePEc:eee:ejores:v:194:y:2009:i:3:p:687-699
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    References listed on IDEAS

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    1. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    2. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "DEA-like models for the efficiency evaluation of hierarchically structured units," European Journal of Operational Research, Elsevier, vol. 154(2), pages 465-476, April.
    3. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2001. "DEA-like models for efficiency evaluations of specialized and interdependent units," European Journal of Operational Research, Elsevier, vol. 132(2), pages 274-286, July.
    4. Jiro Nemoto & Mika Goto, 2003. "Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 191-210, April.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Ouellette, Pierre & Vierstraete, Valerie, 2004. "Technological change and efficiency in the presence of quasi-fixed inputs: A DEA application to the hospital sector," European Journal of Operational Research, Elsevier, vol. 154(3), pages 755-763, May.
    7. Homburg, Carsten, 2001. "Using data envelopment analysis to benchmark activities," International Journal of Production Economics, Elsevier, vol. 73(1), pages 51-58, August.
    8. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, November.
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